Zipf's law for web surfers
type: Item
instance of: scholarly article
title: Zipf's law for web surfers
zbMATH Open document ID: 0991.68622
DOI: 10.1007/PL00011657
author: M. Levene
author: George Loizou
author: José G. Borges
published in: Knowledge and Information Systems
publication date: 2002-07-25T00:00:00Z
review text: One of the main activities of Web users, known as 'surfing', is to follow links. Lengthy navigation often leads to disorientation when users lose track of the context in which they are navigating and are unsure how to proceed in terms of the goal of their original query. Studying navigation patterns of Web users is thus important, since it can lead us to a better understanding of the problems users face when they are surfing. We derive Zipf's rank frequency law (i.e., an inverse power law) from an absorbing Markov chain model of surfers' behavior assuming that less probable navigation trails are, on average, longer than more probable ones. In our model the probability of a trail is interpreted as the relevance (or 'value') of the trail. We apply our model to two scenarios: in the first the probability of a user terminating the navigation session is independent of the number of links he has followed so far, and in the second the probability of a user terminating the navigation session increases by a constant each time the user follows a link. We analyze these scenarios using two sets of experimental data sets showing that, although the first scenario is only a rough approximation of surfers' behavior, the data is consistent with the second scenario and can thus provide an explanation of surfers' behavior.
Mathematics Subject Classification ID: 68U99
Mathematics Subject Classification ID: 68P15
Mathematics Subject Classification ID: 68P20
zbMATH DE Number: 1771456
zbMATH Keywords: Markov chain
zbMATH Keywords: Web navigation
zbMATH Keywords: Zipf's law
MaRDI profile type: Publication
full work available at URL: pl00011657
OpenAlex ID: W1974676676
description: scientific article; zbMATH DE number 1771456